如何使用 matplotlib 生成学生风格的图表？

Question

我目前正在尝试使用 matplotlib。前段时间，我使用 Excel VBA 代码生成图像，如附件。

您会注意到它不是以科学/研究风格呈现的，而是由学生在方格纸上制作的 - 具有三种不同的网格线样式。

有没有一种相当直接的方法可以用 matplotlib 实现这种事情？

Answer 1

这是上述已接受答案的修改版本。 也许有人会觉得这很有帮助

import matplotlib.pyplot as plt
from matplotlib.ticker import MultipleLocator, FormatStrFormatter
import numpy as np
from matplotlib.ticker import FormatStrFormatter

_fontsize_legend = 10
_fontsize = 15

DP = 2

fig = plt.figure(figsize=(12, 12), dpi=100, facecolor='w', edgecolor='k')
##fig = plt.figure()
fig.canvas.draw()
ax = plt.gca()

# set up axis
ax.spines['left'].set_position('zero')
ax.spines['right'].set_color('none')
ax.spines['bottom'].set_position('zero')
ax.spines['top'].set_color('none')
ax.xaxis.set_ticks_position('bottom')
ax.yaxis.set_ticks_position('left')

# draw curve
x = np.arange(-2.5,2.5,0.01)
line, = ax.plot(x, x**2)

#set bounds
ax.set_ybound(-1,7)

## THIS IS THE EDIT
ax.xaxis.set_major_locator(MultipleLocator(1/4))
ax.yaxis.set_major_locator(MultipleLocator(1/4))
ax.xaxis.grid(True,'major',linewidth=2/DP,linestyle='-',color='#d7d7d7',zorder=0)
ax.yaxis.grid(True,'major',linewidth=2/DP,linestyle='-',color='#d7d7d7')

ax.xaxis.set_minor_locator(MultipleLocator( (1/4) / 5 ))
ax.yaxis.set_minor_locator(MultipleLocator( (1/4) / 5 ))
ax.xaxis.grid(True,'minor',linewidth=0.5/DP,linestyle='-',color='#d7d7d7')
ax.yaxis.grid(True,'minor',linewidth=0.5/DP,linestyle='-',color='#d7d7d7')

ax.set_axisbelow(True)
ax.set_aspect('equal')

##ax.axhline(linewidth=0)
##ax.axvline(linewidth=0)

ax.xaxis.set_major_formatter(FormatStrFormatter('%i'))
xticks = ax.xaxis.get_major_ticks()
for i,l in enumerate(xticks):
    if not (i - 1) % 4 == 0:
        xticks[i].label1.set_visible(False)
    else:
        xticks[i].label1.set_fontsize(_fontsize)

ax.yaxis.set_major_formatter(FormatStrFormatter('%i'))
yticks = ax.yaxis.get_major_ticks()
for i,l in enumerate(yticks):
    if not (i - 1) % 4 == 0:
        yticks[i].label1.set_visible(False)
    else:
        yticks[i].label1.set_fontsize(_fontsize)    

figManager = plt.get_current_fig_manager()
figManager.window.showMaximized()
plt.show()

Answer 2

是的，您可以为此使用spines。

import matplotlib.pyplot as plt
from matplotlib.ticker import MultipleLocator, FormatStrFormatter
import numpy as np

fig = plt.figure(1)
ax = fig.add_subplot(111)

# set up axis
ax.spines['left'].set_position('zero')
ax.spines['right'].set_color('none')
ax.spines['bottom'].set_position('zero')
ax.spines['top'].set_color('none')
ax.xaxis.set_ticks_position('bottom')
ax.yaxis.set_ticks_position('left')

# draw curve
x = np.arange(-2.5,2.5,0.01)
line, = ax.plot(x, x**2)

#set bounds
ax.set_ybound(-1,7)

# create grid
#ax.xaxis.set_major_locator(MultipleLocator(1))
#ax.xaxis.set_minor_locator(MultipleLocator(0.2))
#ax.yaxis.set_major_locator(MultipleLocator(1))
#ax.yaxis.set_minor_locator(MultipleLocator(0.2))
#ax.xaxis.grid(True,'minor')
#ax.yaxis.grid(True,'minor')
#ax.xaxis.grid(True,'major',linewidth=2)
#ax.yaxis.grid(True,'major',linewidth=2)

#adjust grid on the 2s
#for idx,loc in enumerate(ax.xaxis.get_majorticklocs()):
    #if loc !=0 and loc % 2 == 0: ax.get_xgridlines()[idx].set_c('r')
#for idx,loc in enumerate(ax.yaxis.get_majorticklocs()):
    #if loc !=0 and loc % 2 == 0: ax.get_ygridlines()[idx].set_c('r')

## THIS IS THE EDIT
ax.xaxis.set_minor_locator(MultipleLocator(0.2))
ax.yaxis.set_minor_locator(MultipleLocator(0.2))
ax.xaxis.grid(True,'minor',linewidth=2)
ax.yaxis.grid(True,'minor',linewidth=2)

minor_grid_lines = [tick.gridline for tick in ax.xaxis.get_minor_ticks()]
for idx,loc in enumerate(ax.xaxis.get_minorticklocs()):
    if loc % 2.0 == 0: minor_grid_lines[idx].set_c('r' )
    elif loc % 1.0 == 0: minor_grid_lines[idx].set_c('g' )
    else: minor_grid_lines[idx].set_c( 'b' )

plt.show()

Answer 3

只是另一个想法 - 我也尝试使用次要网格线来完成所有操作（除了有助于我理解的任何其他内容），但它没有正确枚举，毫无疑问是由于 get_minorticklocs 和 ax.get_xgridlines。抱歉，提前谢谢...

格德斯

import matplotlib.pyplot as plt 
from matplotlib.ticker import MultipleLocator, FormatStrFormatter 
import numpy as np 

fig = plt.figure(1) 
ax = fig.add_subplot(111) 

# set up axis 
ax.spines['left'].set_position('zero') 
ax.spines['right'].set_color('none') 
ax.spines['bottom'].set_position('zero') 
ax.spines['top'].set_color('none') 
ax.xaxis.set_ticks_position('bottom') 
ax.yaxis.set_ticks_position('left') 

# draw curve 
x = np.arange(-2.5,2.5,0.01) 
line, = ax.plot(x, x**2) 

#set bounds 
ax.set_ybound(-1,7) 

# create grid 
ax.xaxis.set_minor_locator(MultipleLocator(0.2)) 
ax.yaxis.set_minor_locator(MultipleLocator(0.2)) 
ax.xaxis.grid(True,'minor',linewidth=2) 
ax.yaxis.grid(True,'minor',linewidth=2) 

#adjust grid on the 2s 
for idx,loc in enumerate(ax.xaxis.get_minorticklocs()):
    if loc % 2 == 0: ax.get_xgridlines()[idx].set_color('r')
    if loc % 1 == 0: ax.get_xgridlines()[idx].set_color('g')
    if loc % 0.2 == 0: ax.get_xgridlines()[idx].set_color('b')

for idx,loc in enumerate(ax.yaxis.get_majorticklocs()): 
    if loc % 2 == 0: ax.get_ygridlines()[idx].set_c('b') 

plt.savefig('spines3.png',dpi=300)